Applied Scientist Ii, Search Query Understanding

Amazon Amazon · Big Tech · Irvine, CA · Applied Science

Applied Scientist II role focused on leveraging LLMs and AI techniques to improve Amazon's search engine and shopping experience. The role involves designing, implementing, and managing scalable ML models, with a focus on RAG and LLM inference optimizations. Requires a PhD or Master's with experience in ML/AI and programming.

What you'd actually do

  1. Collaborate with cross-functional teams to identify requirements for ML model development, focusing on enhancing mission understanding through innovative AI techniques, including retrieval-Augmented Generation or LLM in general.
  2. Design and implement scalable ML models capable of processing and analyzing large datasets to improve search and shopping experiences. Must have a strong background in machine learning, AI, or computational sciences.
  3. Lead the management and experiments of ML models at scale, applying advanced ML techniques to optimize science solution.
  4. Serve as a technical lead and liaison for ML projects, facilitating collaboration across teams and addressing technical challenges. Requires strong leadership and communication skills, with a PhD in Computer Science, Machine Learning, or a related field.

Skills

Required

  • PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
  • Experience programming in Java, C++, Python or related language
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Nice to have

  • Experience using Unix/Linux
  • Experience in professional software development

What the JD emphasized

  • PhD in Computer Science, Machine Learning, or a related field
  • strong background in machine learning, AI, or computational sciences
  • LLM inference optimizations
  • Retrieval Augmented Generation (RAG)

Other signals

  • LLMs
  • search
  • shopping experience
  • ML models